Eurosense (Belgium)

The European Water Framework Directive (2000/60/EC) identifies "Priority Substances" (PS) as those posing a significant risk to or via the aquatic environment. Both reliable exposure data and a reliable Predicted No Effect Concentration (PNEC) are necessary for a robust risk assessment. Unfortunately, the exposure datasets used to evaluate candidate PS contain a large proportion of undetected or unquantified samples. This highlights the left-censored characteristics (i.e., having a high proportion of unquantified results) of many of these datasets. Without appropriate consideration of these non-detects, the risk assessment becomes meaningless, since it does not provide objective evidence that exposure occurs above the relevant PNEC over wide areas or at a significant number of sites. This article is protected by copyright. All rights reserved.

Intelligence delivered by earth observation (EO) satellites performs a vital role in supporting ICT enabled urban governance, and the creation of decision making tools delivering integrated urban planning. This paper reviews the DECUMANUS project experience, detailing the development of the EO derived tools, and evaluating the service products that facilitate the deployment of top-down expertise in land use planning. The central purpose of the paper is to assess the potential for use of these DECUMANUS high resolution EO images and data, also to support bottom-up participatory planning, promoting co-design. It is concluded: 1) EO derived images and associated data offer great opportunity to deliver top-down decision making tools, which combined with auxiliary data, including participatory sensing data, effectively support integrated urban planning; 2) EO derived images also offer substantial potential as communication tools, enabling citizens to make more informed and responsible choices and participate in co-designed urban planning.

For modelling the spatial distribution of malaria incidence, accurate and detailed information on population size and distribution are of significant importance. Different, global, spatial, standard datasets of population distribution have been developed and are widely used. However, most of them are not up-to-date and the low spatial resolution of the input census data has limitations for contemporary, national- scale analyses. The AfriPop project, launched in July 2009, was initiated with the aim of producing detailed, contemporary and easily updatable population distribution datasets for the whole of Africa. High-resolution satellite sensors can help to further improve this dataset through the generation of high-resolution settlement layers at greater spatial details. In the present study, the settlement extents included in the MALAREO land use classification were used to generate an enhanced and updated version of the AfriPop dataset for the study area covering southern Mozambique, eastern Swaziland and the malarious part of KwaZulu-Natal in South Africa. Results show that it is possible to easily produce a detailed and updated population distribution dataset applying the AfriPop modelling approach with the use of high-resolution settlement layers and population growth rates. The 2007 and 2011 population datasets are freely available as a product of the MALAREO project and can be downloaded from the project website.

A method for transfer function calculation is described that derives its economy from the symmetry of the autocorrelation to double the number of lags. The imbalance in the number of lags between autocorrelations and cross-correlations is restored by calculating the negative lags of the cross-correlation without any extra computations. With both positive and negative lags available, the symmetry and periodicity constraints of the fast Fourier transform can be taken into account, and windowing the cross-correlation sequence is less ambiguous. This greatly increases the accuracy and convergence of the computed transfer function. Since the statistical significance of the transfer function estimate is higher, it is possible to obtain the transfer function using shorter data sequences. These last advantages more than outweigh the increase in resolution.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>